nonlinear model predictive control theory and algorithms communications and control engineering

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Nonlinear Model Predictive Control

Author : Lars Grüne
ISBN : 9783319460246
Genre : Technology & Engineering
File Size : 58. 63 MB
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This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. The second edition has been substantially rewritten, edited and updated to reflect the significant advances that have been made since the publication of its predecessor, including: • a new chapter on economic NMPC relaxing the assumption that the running cost penalizes the distance to a pre-defined equilibrium; • a new chapter on distributed NMPC discussing methods which facilitate the control of large-scale systems by splitting up the optimization into smaller subproblems; • an extended discussion of stability and performance using approximate updates rather than full optimization; • replacement of the pivotal sufficient condition for stability without stabilizing terminal conditions with a weaker alternative and inclusion of an alternative and much simpler proof in the analysis; and • further variations and extensions in response to suggestions from readers of the first edition. Though primarily aimed at academic researchers and practitioners working in control and optimization, the text is self-contained, featuring background material on infinite-horizon optimal control and Lyapunov stability theory that also makes it accessible for graduate students in control engineering and applied mathematics.

Economic Model Predictive Control

Author : Matthew Ellis
ISBN : 9783319411088
Genre : Technology & Engineering
File Size : 42. 59 MB
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This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes.In addition to being mathematically rigorous, these methods accommodate key practical issues, for example, direct optimization of process economics, time-varying economic cost functions and computational efficiency. Numerous comments and remarks providing fundamental understanding of the merging of process economics and feedback control into a single framework are included. A control engineer can easily tailor the many detailed examples of industrial relevance given within the text to a specific application. The authors present a rich collection of new research topics and references to significant recent work making Economic Model Predictive Control an important source of information and inspiration for academics and graduate students researching the area and for process engineers interested in applying its ideas.

Modelling And Control Of Dynamic Systems Using Gaussian Process Models

Author : Juš Kocijan
ISBN : 9783319210216
Genre : Technology & Engineering
File Size : 22. 77 MB
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This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.

Handbook Of Model Predictive Control

Author : Saša V. Raković
ISBN : 9783319774893
Genre : Science
File Size : 39. 19 MB
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Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part of this book addresses the solution of optimization problems in “real” time for model-predictive control. The theory and applications of control theory often influence each other, so the last section of Handbook of Model Predictive Control rounds out the book with representative applications to automobiles, healthcare, robotics, and finance. The chapters in this volume will be useful to working engineers, scientists, and mathematicians, as well as students and faculty interested in the progression of control theory. Future developments in MPC will no doubt build from concepts demonstrated in this book and anyone with an interest in MPC will find fruitful information and suggestions for additional reading.

Nonlinear Model Predictive Control

Author : Lalo Magni
ISBN : 9783642010934
Genre : Technology & Engineering
File Size : 41. 19 MB
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Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.

Distributed Model Predictive Control

Author : Aswin N. Venkat
ISBN : WISC:89097475362
Genre :
File Size : 42. 28 MB
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Identification And Control Using Volterra Models

Author : F.J.III Doyle
ISBN : 9781447101079
Genre : Technology & Engineering
File Size : 43. 10 MB
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This book covers recent results in the analysis, identification and control of systems described by Volterra models. Topics covered include: qualitative behavior of finite Volterra models compared and contrasted with other nonlinear model classes, structural restrictions and extensions to Volterra model class, least squares and stochastic identification approaches, model inversion issues, and direct synthesis and model predictive control design, guidelines for practical applications. Examples are drawn from Chemical, Biological and Electrical Engineering. The book is suitable as a text for a graduate control course, or as a reference for both research and practice.

Pid And Predictive Control Of Electrical Drives And Power Converters Using Matlab Simulink

Author : Liuping Wang
ISBN : 9781118339473
Genre : Science
File Size : 25. 23 MB
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A timely introduction to current research on PID andpredictive control by one of the leading authors on thesubject PID and Predictive Control of Electric Drives and PowerSupplies using MATLAB/Simulink examines the classical controlsystem strategies, such as PID control, feed-forward control andcascade control, which are widely used in current practice. The authors share their experiences in actual design andimplementation of the control systems on laboratory test-beds,taking the reader from the fundamentals through to moresophisticated design and analysis. The bookcontains sections on closed-loop performance analysis in bothfrequency domain and time domain, presented to help the designer inselection of controller parameters and validation of the controlsystem. Continuous-time model predictive control systems aredesigned for the drives and power supplies, and operationalconstraints are imposed in the design. Discrete-time model predictive control systems are designed basedon the discretization of the physical models, which will appeal toreaders who are more familiar with sampled-data control system.Soft sensors and observers will be discussed for low costimplementation. Resonant control of the electric drives andpower supply will be discussed to deal with the problems of bias insensors and unbalanced three phase AC currents. Brings together both classical control systems and predictivecontrol systems in a logical style from introductory through toadvanced levels Demonstrates how simulation and experimental results are usedto support theoretical analysis and the proposed designalgorithms MATLAB and Simulink tutorials are given in each chapter to showthe readers how to take the theory to applications. Includes MATLAB and Simulink software using xPC Target forteaching purposes A companion website is available Researchers and industrial engineers; and graduate students onelectrical engineering courses will find this a valuableresource.

American Institute Of Chemical Engineers Symposium Series

Author : American Institute of Chemical Engineers
ISBN : 0816907412
Genre : Chemical engineering
File Size : 37. 82 MB
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Proceedings Tencon 93

Author : Institute of Electrical and Electronics Engineers. Beijing Section
ISBN : 780003285X
Genre : Technology & Engineering
File Size : 42. 18 MB
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